Volume : 2, Issue : 4, April - 2013

Estimation of Storage of Sukhi Reservoir Using ANN Techniques

Daivakshi Shastri, B. M. Vadher, Dr. S. M. Yadav

Abstract :

Hydrologic forecasting plays an ever increasing role in water resource management, as engineers are required to make component forecasts of natural inflows to reservoirs for numerous purposes. Prediction for hydrologic events has always been an important issue for optimizing and planning the whole system. In this study, two different ANN (Artificial Neural Networks) techniques (Generalized Feed Forward network and Multilayer Perceptron) were used for Sukhi reservoir project. A total of 22 years of historical data were used to train and test the networks. To evaluate the accuracy of the proposed model, the Mean Squared Error (MSE) and the Correlation Coefficient (CC) were employed and found the network to be cross validated and trained properly for both models. The developed model shows good agreement with actual observation.